{"id":"W3114600769","doi":"10.1080/03155986.2020.1857629","title":"A dual-level stochastic fleet size and mix problem for offshore wind farm maintenance operations","year":2020,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Maritime Transport Emissions and Efficiency","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Offshore wind power; Solver; Operations research; Computer science; Dual (grammatical number); Subsidy; Stochastic programming; Term (time); Wind power; Mathematical optimization; Engineering; Economics; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009038986,0.0001230763,0.0001478111,0.00005640833,0.000735161,0.0004317362,0.0001170705,0.00007897404,0.0003197043],"category_scores_gemma":[0.0004469285,0.00009766469,0.00002546241,0.0002712953,0.0001860108,0.001065993,0.0001017645,0.0001663941,0.00009283853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005711004,"about_ca_system_score_gemma":0.0001093161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004076494,"about_ca_topic_score_gemma":0.00006489672,"domain_scores_codex":[0.9983679,0.00003087916,0.0004849208,0.0001862653,0.0006250319,0.0003050261],"domain_scores_gemma":[0.9991896,0.0001898211,0.00004987382,0.0001025844,0.000202859,0.0002652595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006948224,0.0002027192,0.009314776,0.001509642,0.00009799797,0.00000694607,0.03581752,0.6343317,0.004667331,0.2225018,0.05353231,0.03732245],"study_design_scores_gemma":[0.001869901,0.0004498803,0.02146962,0.0001205606,0.00001027357,0.00004857476,0.003606852,0.7057988,0.00005329834,0.0001303492,0.2660367,0.0004051911],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.644514,0.0003874066,0.2296091,0.02486591,0.0003653106,0.01466198,0.002979948,0.0002154085,0.08240096],"genre_scores_gemma":[0.9946057,0.00001944369,0.00271985,0.0005175818,0.00006445414,0.0002410448,0.0001350257,0.00000739753,0.001689564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3500917,"threshold_uncertainty_score":0.5654338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05298775210512158,"score_gpt":0.3035127552042682,"score_spread":0.2505250030991466,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}